CN102622534B - A kind of DNA high pass sequencing data bearing calibration detected for gene expression - Google Patents

Abstract

The invention belongs to the field of molecular biological information detection. Specifically, it is a correction method for improving the accuracy of gene expression detection data obtained by DNA high-throughput sequencing. The invention includes the following steps: (1) collecting gene expression DNA sequencing detection data, and establishing a gene expression DNA high-pass sequencing detection data correction model; (2) collecting gene expression values measured by gene chips; (3) using correlation analysis to determine gene expression high-pass Model parameters in the sequencing correction model; (4) gene expression after determining the model parameter values. The correction model of the DNA high-pass sequencing detection data generates corrected gene expression values. The present invention uses a correction model to estimate and compensate the sequence comparison mapping error existing in the DNA sequencing value, reduces the detection error, and effectively improves the detection accuracy on the basis of giving full play to the high resolution and high precision of the DNA high-pass sequencing detection data sex.

Description

A DNA high-throughput sequencing data correction method for gene expression detection

technical field

The invention belongs to the field of molecular biological information detection. Specifically, it is a correction method for improving the accuracy of DNA high-throughput sequencing gene expression detection data.

Background technique

With the advancement of information science experiment technology, the experimental methods used to obtain molecular biological information are also changing with each passing day. Among them, as an epoch-making molecular biological information detection technology, DNA high-pass sequencing technology has the ability to truly realize high-resolution and high-precision detection of gene expression information of the whole genome.

The gene expression detection principle of DNA high-pass sequencing technology is to directly sequence the target nucleotide sequence reflecting gene expression, and then find the position of the target nucleotide sequence in the reference genome through sequence alignment mapping according to the sequencing results, so as to obtain the position Related gene expression information. Because the target nucleotide sequence is directly sequenced, high-throughput DNA sequencing technology has greatly improved the detection resolution and detection accuracy of gene expression. However, since the sequencing results need to be converted into meaningful gene expression information through sequence comparison and mapping, the measurement of gene expression by high-throughput DNA sequencing is an indirect measurement, and there are principle errors. That is, part of the sequencing results cannot be successfully mapped back to the reference genome, resulting in errors in the detection information. This error will cause the detected value to be smaller than the actual value.

Contents of the invention

The purpose of the present invention is to provide a DNA high-pass method that compensates for the principle sequence alignment and mapping errors that exist when generating DNA sequencing data in gene expression detection, and obtains more accurate gene expression detection on the basis of high resolution and high precision. Correction methods for sequencing data.

The purpose of the present invention is achieved like this:

The method for calibrating DNA high-throughput sequencing data comprises the following steps:

(1) Collect gene expression DNA sequencing detection data, and establish a gene expression DNA high-throughput sequencing detection data correction model:

Z _i ＝(1+β×1/C _i )×Y _i

Among them, Y _i is the measured i-th gene expression high-pass sequencing value, Z _i is the corrected i-th gene expression value, C _i is the conservative value of the DNA region where the gene is located, and β is the model parameter;

(2) Collect the gene expression value measured by the gene chip;

(3) Determine the model parameters in the gene expression high-pass sequencing correction model by correlation analysis: calculate the correlation degree between the gene expression value obtained by the gene expression DNA high-pass sequencing detection data correction model and the gene expression value measured by the gene chip, and determine the correlation value The model parameter β value at the maximum;

(4) Gene expression after determining the model parameter values. The DNA high-throughput sequencing detection data correction model generates corrected gene expression values.

The beneficial effects of the present invention are:

The present invention uses a correction model to estimate and compensate the sequence comparison mapping error existing in the DNA sequencing value, reduces the detection error, and effectively improves the detection accuracy on the basis of giving full play to the high resolution and high precision of the DNA high-pass sequencing detection data sex.

Description of drawings

Fig. 1 is a schematic flow sheet of the present invention;

Figure 2 is a distribution map of the conservative value of the target gene;

Figure 3 is the optimization curve of the calibration model parameters.

Detailed ways

The specific implementation method of the inventive method is as follows:

First, by analyzing the principle error caused by indirect comparison and mapping of DNA high-pass sequencing detection data, a correction model for gene expression DNA high-pass sequencing detection data is established in a targeted manner;

Using the correlation analysis method, another high-throughput gene expression detection experimental method that is complementary to DNA high-throughput sequencing in principle, that is, the data generated by the gene chip method, is used to determine the model parameters. And get the final gene expression DNA high-throughput sequencing detection data correction model. The corrected data generated by the model is better than the uncorrected detection data in accuracy.

1. Calibration model of gene expression DNA high-throughput sequencing data

In the process of obtaining gene expression information by high-throughput DNA sequencing, a step of mapping the sequencing data to the reference genome is required. High-throughput DNA sequencing errors occur when sequencing data cannot be mapped to a reference genome for some reason. Therefore, when using high-throughput DNA sequencing technology to detect gene expression information, the expression detection value is often smaller than the actual value. Among them, the main source of error is that when there are a large number of repetitive sequences in the corresponding gene region, DNA sequencing data will cause mapping failure due to non-one-to-one mapping problems. Therefore, the more repetitive sequences exist in the corresponding gene region, the more serious the error will be.

Based on this, the correction model of gene expression DNA high-throughput sequencing data established by this method is shown in formula 1:

Z _i ＝(1+β×1/C _i )×Y _i (1)

Among them, Y _i is the measured i-th gene expression high-throughput sequencing value. Z _i is the i-th gene expression value after correction. C _i is the conservative value of the DNA region where the gene is located. β is a model parameter. According to the theory of biological evolution, the higher the conservation value of a DNA region, the lower its base repeatability. Therefore, the conservative value is used here to reflect the base repetition degree value of the DNA region.

In the calibration model, the generated value Z _i is always greater than the measured value Y _i . This is mainly due to the consideration that the error caused by the mapping failure in the high-pass sequencing error will make the measured value Y _i tend to be smaller than the true value. In addition, the generated value Z _i is inversely proportional to the conservative value C _i . That is, the larger the value of C _i is, the closer the generated value Z _i is to Y _i . This is consistent with the larger the conservative value, the smaller the adjustment should be.

2. Calculation of the parameters of the calibration model

As another high-throughput detection method for gene expression, the gene chip method is not as good as the DNA high-throughput sequencing method in terms of resolution and detection accuracy, but because it directly detects gene expression, there is no sequence alignment problem. Therefore, Here, the gene chip detection data is used to correct the gene expression detection data of DNA high-throughput sequencing. Specifically, the correlation analysis method is used to obtain the model parameters in the gene expression high-pass sequencing correction model. That is, when the model parameter β takes different values, different high-pass sequencing correction values of gene expression can be obtained. Then, calculate the degree of correlation between the correction value and the expression value measured by the gene chip. When the correlation value reaches the maximum, the corresponding model parameter β value is the optimal value. The corresponding model can generate more accurate gene expression sequencing data.

3. Experimental test

3.1 Data Acquisition

1) Sequencing data

The ChIP-seq technology in DNA high-throughput sequencing can be used to measure and count the number of Pol II proteins in the gene transcription region to directly reflect the gene transcription level. This technology first uses ultrasound to degrade the DNA chain into DNA fragments, then uses a special antibody to capture the Pol II protein bound to the DNA fragment, and then uses precipitation technology (IP) to filter out the DNA fragment containing the antibody, followed by sequencing technology ( seq) to sequence all the filtered DNA fragments and map them back to the DNA through sequence alignment, and finally, according to the position definition of the gene transcription region on the DNA, the measurement and statistics of the Pol II protein quantity in the gene transcription region can be realized.

In this experiment, a total of 4 groups of gene promoter region Pol II sequencing data were used in two common and drug-resistant MCF7 breast cancer cells before and after drug administration. The data uses ChIP-seq technology in DNA high-throughput sequencing to measure and count the number of Pol II proteins in the gene promoter region, so as to directly reflect the gene expression level.

2) Gene chip data

In this experiment, the gene expression data obtained by gene chip ChIP-chip technology was used for correlation analysis with the gene expression sequencing data. The data is for the same two common and drug-resistant MCF7 breast cancer cells, a total of 4 groups of gene expression detection data before and after drug addition. The gene chip uses the Human Genome U133Plus 2.0Array chip from Affymetrix, which can detect the expression information of 38,500 genes in the human genome at one time.

3) Gene conservation value data

The DNA nucleotide sequence conservation value data used in this experiment was downloaded from UCSC, a large public database of biological information. The conservative value data is generated by comparing the nucleotide sequences of 44 vertebrate genomes with the human genome nucleotide sequences.

4) Gene sequence data

The DNA nucleotide sequence data used in this experiment were also downloaded from UCSC, a large public database of biological information.

3.2 DNA high-throughput sequencing data correction

First, the completeness of gene expression sequencing data, gene chip data and conservative value data was analyzed, and 9424 genes with the above complete information were obtained.

Subsequently, the conservation values of these gene regions were calculated based on the DNA nucleotide sequence conservation value data. Since the sequencing data used in this experiment is the measurement and statistics of the number of Pol II proteins in the gene promoter, we also use the conservative value sum of the same region to represent the conservative value of this region. The resulting conservative value distribution is shown in Figure 2. In the figure, the horizontal axis is the conservative value, and the vertical axis is the number of times.

Finally, the method introduced in the present invention is used to process the gene expression DNA high-throughput sequencing data. During the processing, the correlation between the gene expression sequencing data and the gene chip detection data was used to optimize the value of the model parameter β. The optimization process is shown in Figure 3. Figure 3 includes cells under 4 different experimental conditions. They are: A: common breast cancer cells before drug addition B: common breast cancer cells after drug addition C: drug-resistant breast cancer cells before drug addition D: drug-resistant breast cancer cells after drug addition. In Fig. 3, the horizontal axis is the value of the model parameter β, and the vertical axis is the correlation degree value between the corrected gene sequencing data and gene chip data. During the correction process, as the β value starts to increase from 0, the correlation degree value increases rapidly, and when the β value takes a certain value, it reaches the extreme value. When the β value continues to increase, the correlation degree value decreases due to over-correction. It can be seen from the figure that, compared with no correction, the degree of correlation between the corrected gene sequencing data and the gene chip data is significantly improved. This shows that using the method proposed in the present invention to correct the sequencing data has achieved more reasonable results. The model corresponding to the optimal value of β is the final calibration model of the sequencing data. Table 1 shows the optimal parameter β value of the processing model for a total of 4 groups of gene sequencing data before and after adding drugs to two common and drug-resistant MCF7 breast cancer cells using this method.

Table 1 Optimal parameter values of the calibration model

In the present invention, the base sequencing results obtained by DNA sequencing technology need to be converted into meaningful gene expression information through sequence comparison and mapping with the base sequence of the reference genome. When part of the sequencing results cannot be successfully mapped back to When referring to the genome, it will lead to errors in the detection information. According to the theory of biological evolution, the higher the conservation value of a DNA region, the lower its base repetition rate, and the higher the success rate of DNA sequencing data mapping in this region. Therefore, conservative values are used in the model to reflect the degree of base repetition in DNA regions and the resulting alignment and mapping errors.

Since another whole-genome gene expression detection technology means—gene chip technology is not as good as DNA sequencing technology in terms of detection resolution, but there is no comparison and mapping link, therefore, the present invention analyzes two different methods from DNA sequencing and gene chip. Correlation analysis is performed on the gene expression detection data generated by independent channels to determine the parameters of the correction model, and finally realize the correction of the DNA sequencing gene expression detection data.

Claims (1)

1. A DNA high-throughput sequencing data correction method for gene expression detection is characterized in that it comprises the following steps: (1) Collect gene expression DNA sequencing detection data, and establish a gene expression DNA high-throughput sequencing detection data correction model: Z _i ＝(1+β×1/C _i )×Y _i Among them, Y _i is the measured i-th gene expression high-pass sequencing value, Z _i is the corrected i-th gene expression value, C _i is the conservative value of the DNA region where the gene is located, and β is the model parameter; (2) Collect the gene expression value measured by the gene chip; (3) Determine the model parameters in the gene expression high-pass sequencing correction model by correlation analysis: calculate the correlation degree between the gene expression value obtained by the gene expression DNA high-pass sequencing detection data correction model and the gene expression value measured by the gene chip, and determine the correlation value The model parameter β value at the maximum; (4) Gene expression after determining the model parameter values. The DNA high-throughput sequencing detection data correction model generates corrected gene expression values.